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Metal-organic frameworks (MOFs) are structures with high surface area that can be used to remove heavy metals (HMs) efficiently from the environment. The effect of MOFs on HMs removal from contaminated soils has not been already investigated. Monometallic MOFs are easier to synthesize with high efficiency, and it is also important to compare their structures. In the present study, Zn-BTC, Cu-BTC, and Fe-BTC as three metal-trimesic acid MOFs were synthesized from the combination of zinc (Zn), copper (Cu), and iron (Fe) nitrates with benzene-1,3,5-tricarboxylic acid (H3BTC) by solvothermal method. BET analysis showed that the specific surface areas of the Zn-BTC, Cu-BTC, and Fe-BTC were 502.63, 768.39 and 92.4 m2g-1, respectively. The synthesized MOFs were added at the rates of 0.5 and 1% by weight to the soils contaminated with 100 mgkg-1 of Zn, nickel (Ni), lead (Pb), and cadmium (Cd). Then quinoa seeds were sown in the treated soils. According to the results, the uptakes of all four HMs by quinoa were the lowest in the Cu-BTC 1% treated pots and the lowest uptakes were observed for Pb in shoot and root (4.87 and 0.39, μgpot-1, respectively). The lowest concentration of metal extracted with EDTA in the post-harvest soils was for Pb (11.86 mgkg-1) in the Cu-BTC 1% treatment. The lowest metal pollution indices were observed after the application of Cu-BTC 1%, which were 20.29 and 11.53 for shoot and root, respectively. With equal molar ratios, highly porous and honeycomb-shaped structure, the most crystallized and the smallest constituent particle size (34.64 nm) were obtained only from the combination of Cu ions with H3BTC. The lowest porosity, crystallinity, and a semi-gel like feature was found for the Fe-BTC. The synthesized Cu-BTC showed the highest capacity of stabilizing HMs, especially Pb in the soil compared to the Zn-BTC and the Fe-BTC. The highly porous characteristic of the Cu-BTC can make the application of this MOF as a suitable environmental solution for the remediation of high Pb-contaminated soils. [ABSTRACT FROM AUTHOR]

The rapid depletion of natural resources and growing awareness of the environmental deterioration have made sustainability one of the key elements enabling contemporary businesses to thrive. Among the most crucial sustainable practices is the application of Green IT due to the wide use of IT in various business sectors to enhance the performance of businesses. Green Information Technology (IT) has emerged as a vital IT governance concern to promote environmentally-friendly IT use and ecologically responsible business processes. according to various researches in green information technology, this research aims to design a green information technology using Meta-synthesis method. In order to design and explain a comprehensive model, all factors of green information technology have been identified through systematic literature review using 189 papers and content analysis. Then the importance and priority of each proposed factor was determined using Shannon quantitative method. The results reveal cost reduction, data center layout, employee stewardship and participation are the major factors in green information technology. At the end the research results demonstrate a comprehensive framework for green information technology factors.

Blockchain technology is a disruptive technology that changes business and supply chain models. Using distributed software architecture and advanced computing, blockchain can change the way information is exchanged between actors in the chain. Blockchain technology provides a platform for solving the problem of tracking product information in supply chain management. Accordingly, the present study aims to provide a model for evaluating the maturity of blockchain technology in the agricultural supply chain. The present research is applied that has been done in three stages. In the first phase, the dimensions of the blockchain are ranked by agricultural experts using the SWARA method. The research experts are 13 faculty members of the department of agriculture active in the field of technology application. In the second phase, a model is designed to evaluate blockchain maturity using each dimension of blockchain technology and maturity dimensions. In the third phase, the proposed model is tested using data collected by a questionnaire in the supply chain of a company active in the agriculture sector. The research findings show that smart contracts, Internet of Things (IoT), and transaction records are of the highest importance among the blockchain dimensions. Also, the supply chain under study is in a good condition in digital documents. Theoretically, the originality aspect of the research is that it determines the importance of blockchain dimensions in the field of agriculture and from an applied point of view, it introduces the maturity model of blockchain in supply chain management.

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome.

Objective: Knowledge management (KM) is a concept of managing knowledge in the company. The implementation of concept has different levels in each company. Organizations implement KM practices and technologies based on the promise of increasing their effectiveness, efficiency, and competitiveness. The concept of maturity can be used for defining the state of effectiveness of an organization or the state of its capability and competency in managing the processes, programs or projects effectively. KM maturity is a guide or measure of the company's position in managing of knowledge. The multi-criteria decision making (MCDM) is widely used method to evaluate criteria that are typically multiple. crisp decision-making method is not appropriate because many of the maintenance goals taken as criteria are non-monetary and difficult to be quantified. Type-2 fuzzy sets are used for modeling uncertainty and imprecision in a better way because of fuzzy membership function. Some fuzzy multicriteria methods have recently been extended by using type-2 fuzzy sets. Analytic Hierarchy Process (AHP) is a widely used multicriteria method that can take into account various and conflicting criteria at the same time. Therefore, the aim of this study is to evaluate KM maturity using Analytic Hierarchy Process method under interval type-2 fuzzy environment. Methodology: This research is a descriptive survey. KM dimensions were ranked by a panel of experts, which consists of seven members. Experts panel consist of faculty of management who published papers and books in KM field. To clarify the evaluation process, an IT company is taken as a case and using APQC's (American Productivity and Quality Center) model. APQC’s Levels of KM maturity provide a road map for moving from immature, inconsistent KM activities to mature; disciplined approaches aligned with strategic business imperatives. The survey sample population consisted of 273 employees and managers of the case. Findings: According to fuzzyanalytic hierarchy process results KM process (0.24), technology (0.23), evaluation (0.20), KM culture (0.18) and leadership (0.15) are the most important dimensions of KM maturity. it was revealed that the importance of KM processes could be ordered as following: Knowledge Capturing, Knowledge Creation, Knowledge Transferring, and Knowledge Reusing. Also, the results showed the case is located on third level of KM maturity (standardize). The primary focus at Level 3 is to manage the KM strategy, processes, and approaches identified and defined in Level 2. Conclusion: An important part of the results revealed how to use fuzzy analytic hierarchy process for evaluating KM maturity and the importance of processes and technology in KM maturity. In addition, the case is located on third level of KM maturity; during this third level, the KM team often evolves into a KM Center of Excellence with oversight responsibilities for the KM approaches and processes. Oversight includes identifying opportunities to apply select KM approaches and processes, securing funding and resources for the pilots, marketing and communicating the strategy, implementing a change management strategy, and refining the KM approaches and processes into standard, replicable methodologies.

Introduction: Blockchain can be defined as a distributed and immutable digital ledger that provides data transparency and user privacy. According to the applications of blockchain, conducting of each application needs planning and cost management. This study endeavored to identify and rank the uses of blockchain technology in healthcare. Methods: This descriptive study was done in the winter semester of the academic year of 2020. In the first phase, the uses of blockchain technology in healthcare were recognized from library resources using qualitative content analysis. In the next phase, these uses were prioritized by a panel of experts with 17 members. Then, we used fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method for ranking the uses of blockchain in healthcare. Results: Electronic health records (0.43), smart contracts (0.21), internet of things infrastructure (0.15), information security and privacy (0.08), administrative management (0.06), and electronic voting (0.04) were the important applications of blockchain technology in healthcare. Conclusion: Finding of this study show that blockchain technology has important applications in healthcare electronic health records and smart contracts. Therefore, health system policymakers should provide the infrastructure for implementation of blockchain technology among medical and health organizations. This study can contribute to the research in the blockchain field, and enrich the literature on the application of this technology in healthcare.

Background and Aim: Virtual Reality and Augmented Reality are immersive technologies that integrate virtual and real-world elements. These technologies have been used to help and improve human capabilities in many fields. Virtual and augmented systems are used in various medical situations. They are effective options in most stages of patient treatment and performing medical procedures. Therefore, the purpose of this study is to investigate the applications of virtual and augmented reality technologies in the field of medicine and rank them. Materials and Methods: This applied research was conducted in two phases using mixed-method approach in 2020. Library resources were used in the qualitative phase and a questionnaire in the quantitative phase. The applications of virtual and augmented reality technologies were ranked by a panel of experts having 13 members. Finally, Stepwise Weight Assessment Ratio Analysis(SWARA) method was used to rank the applications of technologies in medicine. Results: The results of SWARA method showed that education (0.252), surgery (0.216), health games (0.188), patient control and diagnosis (0.186), and pharma (0.158) were the most important applications of virtual and augmented reality in medicine. Conclusion: Based on the results of this study, it can be acknowledged that medical education and surgery are the most important applications of augmented and virtual reality technologies in medicine. Therefore, policymakers and hospital managers must use this ranking for the development of virtual and augmented reality technologies in their organization to provide better services to the customers and patients.

Covid-19 presents many social and economic challenges and exacerbates existing ones. One of these challenges is global poverty. Prior to the epidemic, poverty affected the rural population traditionally. Global poverty can spread to urban areas now with COVID-19 outbreak. Poverty increased in the United States in 2020 as the coronavirus outbreak, affecting the economy and rising unemployment. New figures confirm that the recession may have widened the gap between rich and poor, with those at the bottom of the economic ladder suffering the most, such as the rural population. In this study, we examine the relationship between Covid outbreak, governance and economic performance and its impact on number in poverty. To this end, data from the Center for American Progress is analyzed over 10 years (from 2011–2020) among the 49 states in America through spatial econometric techniques for panel data. The effect of each state's condition was examined on neighboring states. The results showed that the governance index (with a negative sign) and Income inequality variable (with a positive sign), have the greatest impact on poverty. The unemployment, Gender wage gap, Hunger and food insecurity, Health insurance, Population and Higher education also have an impact on poverty. The policy recommendations of this study are that because the variable of governance (accountability and responsibility of the government to compensate for the damage caused by the covid outbreak) is one of the most effective variables to control poverty. [ABSTRACT FROM AUTHOR]

Background and Objectives: The Internet of Things (IoT) refers to billions of physical devices around the world that are now connected to the internet, all collecting and sharing data. The IoT has been widely applied to interconnect available medical resources and provide reliable, effective and smart healthcare service to the people. The social acceptance of IoT applications and services strongly deepens on the trustworthiness of information and the protection of private data. The marked expansion of the IoT specific technologies has presented daunting ethical challenges. Therefore, the present study aimed to identify the ethical issues of IoT in medical sciences in Iran. Methods: The current study was conducted in two phases using the mixed-method approach in winter 2020. In the first phase, the ethical issues of the IoT were identified by library search and assessed by the content analysis. In the second phase, ethical issues were ranked by a panel of experts, including 15 IT experts who worked in medical universities in Iran. The Stepwise Weight Assessment Ratio Analysis (SWARA) method was used for ranking the ethical issues of IoT. Results: The obtained results revealed the importance of informed consent (0.259), privacy (0.227), information security (0.195), trust (0.171), and physical safety (0.148) in ethical issues of IoT. Conclusion: As evidenced by the obtained results, informed consent and privacy were the most important ethical issues in IoT. Moreover, IoT devices that target or profile peopleschr('39') information without their knowledge or consent could be interpreted as infringing upon their privacy. The users of these devices should be able to intentionally manage the transformative effects of the technologies that influence and shape their development. Moreover, the health sector policymakers should be aware of the ethical commitment to using IoT technology.

The physiological functions of natural killer (NK) cells in human immunity and reproduction depend upon diverse interactions between killer cell immunoglobulin-like receptors (KIRs) and their HLA class I ligands: HLA-A, HLA-B, and HLA-C. The genomic regions containing the KIR and HLA class I genes are unlinked, structurally complex, and highly polymorphic. They are also strongly associated with a wide spectrum of diseases, including infections, autoimmune disorders, cancers, and pregnancy disorders, as well as the efficacy of transplantation and other immunotherapies. To facilitate study of these extraordinary genes, we developed a method that captures, sequences, and analyzes the 13 KIR genes and HLA-A, HLA-B, and HLA-C from genomic DNA. We also devised a bioinformatics pipeline that attributes sequencing reads to specific KIR genes, determines copy number by read depth, and calls high-resolution genotypes for each KIR gene. We validated this method by using DNA from well-characterized cell lines, comparing it to established methods of HLA and KIR genotyping, and determining KIR genotypes from 1000 Genomes sequence data. This identified 116 previously uncharacterized KIR alleles, which were all demonstrated to be authentic by sequencing from source DNA via standard methods. Analysis of just two KIR genes showed that 22% of the 1000 Genomes individuals have a previously uncharacterized allele or a structural variant. The method we describe is suited to the large-scale analyses that are needed for characterizing human populations and defining the precise HLA and KIR factors associated with disease. The methods are applicable to other highly polymorphic genes.

The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.

Background: The fourth industrial revolution consists of combining network devices with cloud computing methods and analyzing large data and artificial intelligence, which makes it possible to call such an infrastructure smart. In a Smart Hospital, all things and devices are designed to be connected and integrated, thus achieving better patient care, increasing efficiency and reducing time waste. Therefore, the aim of this paper was to recognize the components of smart hospital based on disruptive technologies of industry 4.0. Materials and Methods: This applied research has been done in two phases using qualitative approach in winter 2019. In the first step, the components of smart hospital were recognized from previous studies. In the second step, research experts evaluate conceptual model by Delphi method. The expert panel consists of 15 individuals active in information technology in healthcare according to targeted sampling. Results: According to research results the main components of smart hospital are eight technologies: Internet of things technology, robotic, blockchain technology, cloud computing, big data, augmented and virtual reality technology, additive manufacturing and artificial intelligence. Conclusion: According to components of smart hospital, Hospitals managers should equip their organization and adopt process and equipment by disruptive technologies. Due to sanctions, investment in Iranian knowledge-based companies active in new technologies field and Joint venture with them can be a suitable solution for healthcare policymakers.

Background and Aim: The Fog Computing is a highly virtualized platform that provides storage, computing and networking services between the Cloud data centers and end devices. Fog computing fits the characteristics of real-time health monitoring systems. In such systems, a large amount of data is acquired from a multitude of bio and environmental sensors. On the other hand, its distribution and open structure makes it vulnerable and weak to security threats. Therefore, the aim of this paper was to identify the security challenges in healthcare. Materials and Methods: This applied research has been done in three phases using mixed-method approach in 2019. In the first phase, security codes from library resources by content analysis was identified. In the second phase interpretation of experts by Delphi method, Panel of IT experts consists of twelve members who work on healthcare sector was evaluated. Finally, we used Analytic Hierarchy Process method for ranking security codes. Results: According to fuzzy AHP results attacks(0.31), secure communications(0.23), authentication and access control(0.19), trust(0.15) and privacy preservation(0.12) are the most important criteria in security challenges of fog computing. Conclusion: According to the results of this study, secure communications and network attacks are the major challenges in fog computing, because fog nodes are usually deployed in some places with relatively weak protection. They may encounter various malicious attacks. As a result, policymakers should be aware of the role of secure communications and network attacks in fog computing implementation.

The Islamic ethics views dedication to work as a virtue. Social relations at work are encouraged in order to meet one’s needs and establish equilibrium in one’s individual and social life. On the other hand Social capital can facilitate access to information and vital sources in order to promote performance and use environmental opportunities. An organization with powerful social capital can have immediate access to a wide range of information in order to create innovative performance. This capital is an intangible asset to the organizations and successful organizations can use it appropriately and immediately. Accordingly, this research examines the effect of Islamic ethics on social capital with the role of mediator of social responsibility. This research is descriptive survey, in which the questionnaire has been used to collect data. Shiraz University was chosen as an Islamic case. The survey sample consists of 273 randomly taken employees of Shiraz University. Data collected by structural equation software LISREL has been analyzed. The results revealed Islamic ethics has a positive and significant effect on social responsibility and social capital.

Background and Objective: Parents of children with cancer are more susceptible to psychological problems such as anxiety, depression, stress, and generally, mental health risks. This study was done to determine the effectiveness of group acceptance and commitment therapy on self-efficacy among mothers of children with cancer. Methods: This quasi-experimental study was conducted on 30 mothers of children with cancer referring to Children’s Medical Center in Tehran, Iran during 2017. Mothers were non-randomly assigned into intervention and control groups. For gathering the data, the parental self agency measure of Dumka and colleagues (PSAM; 1996) was used. The group acceptance and commitment therapy was offered to subjects in the interventional group for 2-hour in 10 sessions, but the control group's mothers did not receive any intervention. Results: Mean scores of self-efficacy among mothers of children with cancer were 31.40±6.40 and 53.87±13.35 in pre-test and post-test, respectively (P

Background and Aim: MOOC stands for Massive Open Online Course and is an instructional approach that allows hundreds of thousands of students to access -- typically free of charge -- online courses anywhere around the world. The continuous and rapid growth of MOOCs has attracted the attention of educational community and has gained widespread popularity among many universities. Therefore, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, an applied research was conducted to study medical studentschr('39') acceptance to use MOOCs. Materials and Methods: It is a descriptive survey that has been done in 2019. The sample consisted of 367 randomly selected students of Shiraz University of Medical Sciences (SUMS). The data collection tool was a questionnaire, the validity and reliability of which were confirmed. The data were analyzed by SPSS and LISREL 8.8 software. Results: An important part of the results revealed that there was a positive meaningful relationship between "performance expectancy" and "behavioral intention", "effort expectancy" and "behavioral intention", "facilitating conditions" and "use of the system", and "behavioral intention" and "use of the system". Conclusion: According to the results of this study, MOOC managerschr('39') motivation to implement the system effectively strongly depends on the behavioral intention of users, especially studentschr('39') willingness to accept and use the system.

Objective: Organizations require knowledge management (KM) in order to continue their activities and sustainability in their competitive cycles. One of the problems of organizations and managers is the implementation of KM, considering the factors affecting the implementation of KM plays an important role in the success and development of the organization. Meanwhile, the factors affecting the implementation of KM, determining the importance of each of the factors and providing an appropriate framework for their application in KM implementation process play a fundamental role in advancing the organization's goals. The purpose of this research is to identify and rank the factors affecting the implementation of KM by reviewing the past studies. Methodology: Meta-synthesis attempts to integrate results from a number of different but inter-related qualitative studies. In order to identify the factors, all dimensions of KM implementation have been identified through Meta-Synthesis using 335 papers were published in Sciencedirect, SID, Magiran and ElmNet from 2010 to 2018. Then, the importance and priority of each proposed dimension was determined using Shannon quantitative method based on content analysis. Findings: The results of the research in the extension method showed 3 categories (organizational, personal, and environmental), 8 concepts (KM process, organization structure, technology, management, individual, trust, competitive and culture) and 52 codes (knowledge creation (0.016), knowledge identification (0.026), knowledge leadership (0.00), knowledge planning (0.01), knowledge effectiveness (0.024), knowledge sharing (0.039), knowledge evaluation (0.01), knowledge storage (0.02), knowledge learning (0.00), knowledge transparency (0.00), knowledge implementation (0.024), knowledge quality (0.024), KM alignment (0.02), organization strategy (0.016), KM strategies (0.039), employees enrichment (0.01), organizational enrichment (0.00), organizational sources (0.02), financial sources (0.016), organizational environment (0.00), the number of employees (0.016), recruitment (0.00), organizational size (0.016), performance evaluation (0.026), KM system selecting (0.026), employees training (0.031), reverse engineering (0.00), fast upgrade (0.024), flexability (0.032), confidence (0.032), easy implementation (0.026), technological tools(0.01), storage capacity (0.024), information technology infrastructure (0.035), management support (0.035), human resource management (0.039), team working (0.031), participation (0.00), motivation (0.034), justice(0.00), readiness(0.00), concentration (0.00), communication (0.031), employees trust and managers(0.031), employees trust (0.024), competition force (0.016), benchmarking (0.016), world services availability (0.02), best practices (0.01), knowledge base culture (0.01), innovation culture (0.032) and organizational culture (0.044) in KM implementation. Conclusion: A successful KM program will consider more than just technology. An organization should also consider organization culture, leadership, strategic alignment, managers' support, information technology and motivation were identified as the most important factors for success of KM implementation.

Objectives: This study investigated anthropometric changes of national law enforcement officers (LEOs) in 46 years, compared the differences between LEO data and civilian anthropometry, and identified the magnitude of differences in dimensions measured with gear versus semi-nude measurements. Background: The best available 46-year-old anthropometric dataset of LEOs has largely become outdated due to demographic changes. Additionally, anthropometric data of female LEOs and LEO measurements with gear are lacking. Method: Thirty-four traditional body dimensions and 15 with gear measurements of 756 male and 218 female LEOs were collected through a stratified national survey using a data collection trailer that traveled across the U.S. and the data were compared to the LEO anthropometric data from 1975 and existing civilian anthropometric databases. Results: LEO body size and shape have evolved over the past 46 years - an increase of 12.2 kg in body weight, 90 mm in chest circumference, and 120 mm in waist circumference for men. No previous data was available for comparison for females. Compared to civilians, both male and female LEOs have a larger upper body build. LEO gear added 91 mm in waist breadth for men and 120 mm for women, and 11 kg in weight for men and 9 kg for women. Conclusion: The study reveals that equipment design based on the existing civilian datasets or 46-year-old LEO dataset would not accommodate the current LEO population. The new data fill this gap. Application: The differences reported above are important for LEO body gear, vehicle console, and vehicle ingress/egress design. [ABSTRACT FROM AUTHOR]

Background: A standardized method to measure and quantify women's birth experiences is required to study satisfaction of childbirth care. Therefore, this study aimed to translate and culturally adapt the Childbirth Experience Questionnaire (CEQ) for use in Iran. Materials and Methods: This was a cross-sectional study including 203 women who attended 2 hospitals and 2 health centers and met the inclusion criteria in Ahvaz city, between February 2013 and June 2014. After forward and backward translation of the Swedish CEQ into Persian language, content validity was assessed by an expert panel. Scale reliability (internal consistency and test-retest reliability) was assessed with respect to the psychometric properties of the scale. Results: Minor cultural differences were identified and resolved during the translation process. One item was excluded. The intraclass correlation coefficient ranging from 0.63 to 0.90 was satisfactory. Conclusions: The Persian version of the CEQ appears to be valid and reliable; hence, it can be an effective tool in designing childbirth experience interventions and also childbirth care and education interventions for the promotion of positive childbirth experience in Iranian women.

Lung adenocarcinoma with lepidic growth pattern (LPA) is characterized by tumor cell proliferation along intact alveolar walls, and further classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive lepidic predominant adenocarcinoma (iLPA). Accurate diagnosis of lepidic lesions is critical for appropriate prognostication and management as five-year survival in patients with iLPA is lower than in those with AIS and MIA. We aimed to evaluate the accuracy of CT-guided core needle lung biopsy classifying LPA lesions and identify clinical and radiologic predictors of invasive disease in biopsied lesions. Thirty-four cases of adenocarcinoma with non-invasive lepidic growth pattern on core biopsy pathology that subsequently were resected between 2011 and 2018 were identified. Invasive LPA vs. non-invasive LPA (AIS or MIA) was defined based on explant pathology. Histopathology of core biopsy and resected tumor specimens was compared for concordance, and clinical, radiologic and pathologic variables were analyzed to assess for correlation with invasive disease. The majority of explanted tumors (70.6%) revealed invasive disease. Asian race (p = 0.03), history of extrathoracic malignancy (p = 0.02) and absence of smoking history (p = 0.03) were associated with invasive disease. CT-measured tumor size was not associated with invasiveness (p = 0.15). CT appearance of density (p = 0.61), shape (p = 0.78), and margin (p = 0.24) did not demonstrate a significant difference between the two subgroups. Invasiveness of tumors with lepidic growth patterns can be underestimated on transthoracic core needle biopsies. Asian race, absence of smoking, and history of extrathoracic malignancy were associated with invasive disease.